Survey of Attack Graph Analysis Methods from the Perspective of Data and Knowledge Processing
Обзор методов анализа графов атак с точки зрения обработки данных и знаний
2019-12-26
SCID: 54.1/7mpyxvdf
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Bayesian networkMarkov modelattack graph analysisnetwork security assessmentuncertainty analysis
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Abstract (AI)
Attack graph can simulate the possible paths used by attackers to invade the network. By using the attack graph, the administrator can evaluate the security of the network and analyze and predict the behavior of the attacker. Although there are many research studies on attack graph, there is no systematic survey for the related analysis methods. This paper firstly introduces the basic concepts, generation methods, and computing tasks of the attack graph, and then, several kinds of analysis methods of attack graph, namely, graph-based method, Bayesian network-based method, Markov model-based method, cost optimization method, and uncertainty analysis method, are described in detail. Finally, comparative study of the methods and future work are provided. We believe that this work would help the research community to understand the attack graph analysis method systematically.
Key Findings
1
A comparative study of the reviewed methods is presented, together with directions for future research.
2
Attack graphs support network security evaluation and analysis and prediction of potential attacker behavior.
3
It reviews attack graph fundamentals, including core concepts, generation methods, and computational tasks.
4
The paper provides a systematic survey of attack graph analysis methods from a data and knowledge processing perspective.
5
The survey categorizes analysis approaches into graph-based, Bayesian network-based, Markov model-based, cost optimization, and uncertainty analysis methods.
Research Object
attack graphs modeling possible network intrusion paths
Research Subject
analysis methods for evaluating network security and analyzing and predicting attacker behavior
Publication Details
Publication Date
2019-12-26
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